1. Field of the Invention
The present invention relates to the general area of the analysis and interpretation of subsurface regions on the basis of seismic data, and in particular to improving the modelling of subsurface regions by improving the determination of the impedance coefficients of a seismic trace.
2. Description of the Related Art
When appraising or developing an oil or gas field, it is well known to use seismic data to provide information regarding the subsurface region, which can provide information about the presence, location, size, etc, of potential petroleum reservoirs, on the basis of the reflection characteristics of incident waves. Therefore, an analysis or modelling of the structure and properties of the subsurface region is important in making drilling decisions, and a reduction in the uncertainty of such analysis or modelling is particularly advantageous in improving decision making.
Impedance coefficients of a seismic trace are commonly computed with an integration in time of reflection coefficients, wherein the reflection coefficients are themselves usually computed using a sparse spike inversion of the seismic traces.
FIGS. 1(a) to 1(c) show an example of a 1D seismic trace inverted with a sparse spike inversion procedure, and the corresponding impedance coefficients. More particularly, FIG. 1(a) shows a 1D seismic trace, FIG. 1(b) shows corresponding reflection coefficients after a sparse spike inversion, and FIG. 1(c) shows impedance coefficients after an integration in time of the reflection coefficients.
Here, reflection coefficients are sparse spike signals. Since each 1D seismic trace is processed independently from other traces in most sparse spike inversion techniques, the amplitude of the spikes at the same time locations can vary significantly from one trace of reflection coefficients to its immediate neighbors. For example, if two neighboring traces of reflection coefficients computed with a sparse spike inversion are superimposed, the spikes would tend to be at similar time locations, but their amplitudes can vary significantly from one trace to the other.
The corresponding impedance coefficients computed with an integration of the reflection coefficients are piece-wise constant signals, however the value of the constants are very different on a same segment from one trace to another. This is illustrated for 1D signals by FIG. 2, which shows a superimposition of two neighboring traces (‘Trace 1’ and ‘Trace 2’) of impedance coefficients computed with an integration in time of the corresponding neighboring reflection coefficient traces. It can be seen that both signals have very different constant values on each constant segment.
This effect is particularly visible on 2D images of impedance coefficients. FIG. 3(a) shows a 2D image of impedance coefficients from a first dataset (‘the Cyclone dataset’), where the impedance coefficients were integrated from reflection coefficients computed using a sparse spike inversion. The horizontal direction is crossline, and the vertical direction is time. The differences in the coefficients from one trace to another (as represented by the brutal changes in tone in FIG. 3(a)) are artifacts and have no geophysical justifications. To remove these artifacts, the lowest frequencies of impedance coefficients in the time direction should be suppressed or attenuated. This is usually done by filtering low frequencies with a simple low-cut filter, typically at around 1 Hz. However, some important lower frequencies may be lost using this conventional technique, and it is therefore desirable to provide a filtering technique which removes artefacts whilst retaining more information from the lower frequencies, in order to provide an improved determination of impedance coefficients.